Estimating Phase Maps from Partial K-Space Data

Tom Depew¹, Qing-San Xiang¹, ²

Phase can be used to encode information about numerous MRI properties such as magnetic field strength, motion or flow, and temperature. Phase maps are typically obtained by comparing two complex images in which the relative phase is sensitized to the physical quantity of interest. In situations where the phase can be assumed to change smoothly, the two images can be reconstructed from central k-space data to reduce scan time. Here we investigate the effect of truncation artifact associated with this approach and the feasibility of obtaining phase maps by fitting a convolution kernel to various partial k-space coverage patterns.